Working Memory Defects In Patients With Mild Cognitive Impairment

Mild cognitive impairment(MCI)is defined as a condition between normal aging and AD.The annual conversion rate from MCI to Alzheimer’s disease is 5 to 20 percent,and it is irreversible.Therefore,early diagnosis and timely treatment of the symptoms of MCI are particularly important.At present,the economic cost of brain image recognition is high,and the neuropsychological test needs professional medical personnel to operate.There is not yet an experimental paradigm which is convenient and objective enough to distinguish normal aging from MCI.In order to solve this problem,this study adapted the classic working memory "change detection" paradigm to investigate the difference in working memory between the MCI group and the normal aging group,and used EEG technology to understand the neural mechanism of MCI cognitive decline.At the same time,we tried to use machine learning methods to distinguish the MCI population from the normal elderly groupThe 88 cases comprised of 42 participants for MCI group and 46 participants for Normal group.The main results are as follows:(1)The MCI group had lower memory accuracy and memory capacity than control group,and the individual differences in the MCI group were larger;(2)The analysis of brain network connectivity by integrating temporal and spatial information demonstrated that there were obvious differences in brain network connectivity between MCI group and normal aging group.And time dependent brain network connectivity analysis showed the functional connections of brain networks in the early attention stage and memory maintenance stage may be affected by memory strategies;(3)The accuracy of classifying subjects based on brain network connection data can reach more than 90%;(4)At the same time,there was a positive correlation between behavioral performance and cognitive assessment scores in the MCI group,but no such trend was shown in the normal aging group.Currently,it is speculated that the cognitive impairment in the MCI group is not general,so there are large individual differences.This result also reflects that the current working memory paradigm can reflect the differences in the cognitive ability of the subjects.In conclusion,compared with the normal elderly group,the MCI group did have more severe impaired working memory,and the individuals with impaired working memory in the MCI group showed greater variability.There were differences in the functional connections between the MCI group and the normal aging group at different stages of working memory,and the brain network connections in the early attention stage and information maintenance stage were also affected by memory strategies.Finally,it is feasible to distinguish the two groups of people based on the brain network connection information.Based on the change detection task,we evaluated working memory impairment in patients with MCI using objective behavioral indicators and ERP technology,and explored the mechanism of working memory defects in MCI.At the same time,the brain network correlation analysis method was used to classify the two groups,and encouraging results were obtained,demonstrating the possibility of using these objective evaluation criteria to quickly identify patients in a wide range of potential patients,which has a certain positive application significance.